It is popular in WSD to use contextual information in training sense tagged data. Co-occurring words within a limited window-sized context support one sense among the semantically...
In this paper a novel solution to automatic and unsupervised word sense induction (WSI) is introduced. It represents an instantiation of the `one sense per collocation' obser...
We present results that show that incorporating lexical and structural semantic information is effective for word sense disambiguation. We evaluated the method by using precise in...
Takaaki Tanaka, Francis Bond, Timothy Baldwin, San...
An N-gram language model aims at capturing statistical word order dependency information from corpora. Although the concept of language models has been applied extensively to handl...
To support more effective searches in large-scale weaklytagged image collections, we have developed a novel algorithm to integrate both the visual similarity contexts between the...